From 1-5 April, Bielefeld University will be exhibiting at the 2019 Hannover Messe (Hannover Trade Fair) with the Research Institute for Cognition and Robotics (CoR Lab) and the Cluster of Ex-cellence Cognitive Interaction Technology (CITEC). The researchers will be presenting their platforms and applications for machine learning. One example of their work is a new method for quickly adjusting hand prostheses: The system enables flawless control of hand prostheses – even if the measuring electrodes have moved on the user’s skin. This system is one of four presentations by Bielefeld University, one of which belongs to a new start-up company founded by CITEC researchers. “At the trade fair, we will be presenting advanced technologies and example applications for the efficient use of machine learning methods,” says Dr.-Ing. Sebastian Wrede of CoR-Lab, who is coordinating the participation in the trade fair. “These will be demonstrated following the value-added chain: from efficient hardware and software to integrated intelligent systems.”
Algorithm compensates for disturbances
Hand functioning can be partially restored with modern hand prostheses. Electrodes placed on the residual limb measure muscle signals, an algorithm derives the desired hand movement from these signals, and a prosthesis then performs the movement. Such prosthetics, however, are prone to errors, especially if the electrodes move around on the skin. The Machine Learning research group, headed by Professor Dr. Barbara Hammer, has developed a system that compensates for errors caused by displaced electrodes. A machine learning algorithm adapts the control system from how it had been calibrated in the clinic to the new position of the electrode based on everyday use. What makes the system unique is that it gets by with very little data. “This also makes the new process appealing for industry,” says Sebastian Wrede. “Here, too, systems often have to make do with very little sample data.”
As part of the EU project “Legato,” the Cognitronics and Sensor Systems research group has developed an intelligent mirror for smart homes. The project deals with energy-efficient data processing. Controlling in smart homes typically requires a great deal of computing power, and is mostly operated using cloud computing. Bielefeld’s smart mirror is intended to show how machine learning methods can be used onsite to save energy. The mirror recognizes its users and displays personalized information (such as bus schedules or current information about the home). It can be operated using both gestures and speech. And because the mirror processes data locally – not on external company servers – privacy is ensured.
Making robots accessible
The tech start-up “R+” is dedicated to robotics and human-machine interaction. The team innovates products in areas of application ranging from customer support to healthcare. The goal is to relieve workers in their daily work routine by shifting repetitive tasks to robots, thereby freeing up more time for the human worker to do creative or caring tasks. The start-up provides its customers with a system that enables the average person to independently configure robots for their own individual needs. The system allows users to create solutions based on concepts from machine learning, machine vision, and edge computing (local data processing). With this system, the start-up aims to realize its vision of the robot as an service provider accepted in the heart of society.
Source: Bielefeld University